code: def testComputeAverageLossDtype(self, distribution):
      with distribution.scope():
          per_example_loss = constant_op.constant(
              [2.0, 4.0, 6.0], dtype=dtypes.float64
          )
          per_replica_losses = distribution.run(
              nn_impl_distribute.compute_average_loss,
              args=(per_example_loss,),
              kwargs={"sample_weight": 2},
          )
          loss = distribution.reduce(
              "SUM", per_replica_losses, axis=None
          )
          self.assertEqual(loss.dtype, dtypes.float64)
  
imports: from absl.testing import parameterized
  from tensorflow.python.distribute import combinations
  from tensorflow.python.distribute import strategy_combinations
  from tensorflow.python.eager import context
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import errors
  from tensorflow.python.framework import errors_impl
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import nn_impl_distribute
  from tensorflow.python.platform import test
label_desc: Use image node_id 11 for calling the LossUtilitiesTest obj's underlying member method code with example usage: obj.testComputeAverageLossDtype(distribution) without return types